1. Field of Invention
The invention relates to a method for operating a resonance-measuring system, in particular a Coriolis mass flowmeter, wherein the resonance-measuring system includes at least one oscillation element, at least one oscillation driver and at least one oscillation sensor, wherein the oscillation element (is excited to oscillation in at least one eigenform from at least one control in at least one control loop by at least one oscillation driver excited by at least one excitation signal and the excited oscillations of the oscillation element are detected by the oscillation sensors as at least one response signal. In addition, the invention relates to a resonance-measuring system that is operated using such a method.
2. Description of Related Art
Resonance-measuring systems of the type mentioned above have been known for years, not only in the form of Coriolis mass flowmeters, but also in density-measuring devices or level monitors using the tuning fork principle, in quartz scales and band viscometers, among other things. These resonance-measuring systems are connected with a process, wherein the process and the resonance-measuring system are interactive.
In the following, resonance-measuring systems are covered using the example of Coriolis mass flowmeters, which should not be understood as being limiting. Such systems are generally termed resonance-measuring systems, in which information about the determining process variables (indicators) is encoded in the eigenfrequencies and/or such systems in which the working points are placed at the eigenfrequencies of the measuring system. The further developments described in the following can be used on all systems subject to this definition. The measuring tube of a Coriolis mass flowmeter corresponds to the oscillation element of the resonance-measuring system; this particular design of the oscillation element is also not limiting for the general teaching applicable to the resonance-measuring system.
Resonance-measuring systems designed as Coriolis mass flowmeters are used especially in industrial process measurement engineering where mass flows have to be determined with high accuracy. The functionality of Coriolis mass flowmeters is based on at least one measuring tube—oscillation element—with a flowing medium being excited to oscillation by an oscillation driver, wherein the medium having mass reacts to the Coriolis inertia force on the wall of the measuring tube caused due to the two orthogonal speeds—that of the flow and that of the measuring tube. This reaction of the medium on the measuring tube leads to a change of the measuring tube oscillation compared to the non-flow oscillation state of the measuring tube. By gathering these features of the oscillation of the Coriolis measuring tubes with flow, the mass flow through the measuring tube can be determined with high accuracy.
The eigen frequencies of the Coriolis mass flowmeters or the parts capable of oscillation of the Coriolis mass flowmeter are of particular importance, i.e., essentially the eigenfrequencies of the measuring tube, since the working point of the Coriolis mass flowmeter is normally applied to eigenfrequencies of the measuring tube in order to be able to imprint the necessary oscillation for the induction of the Coriolis forces with minimum energy effort. The oscillation executed by the measuring tube has a certain form, which is termed the eigenform of each excitation.
The oscillation behavior of the Coriolis mass flowmeter or measuring tube is determined using different system parameters, for example, using the oscillating masses, the damping and the stiffness of the eigenform of the measuring tube. These system parameters are normally in practice, however, time variant and can potentially change very quickly—or creeping—, which directly influences the quality of the measurement, in particular when the changes of these system parameters are unknown, which can be assumed for the most part. Causes for the changes of these parameters can, for example, be a change in the density of the medium, a change in the operating pressure, the operating state during filling, emptying or during operation with partial filling, a multi-phase flow of the medium—when, for example, liquid and gas-phase media are transported together—and a change in the temperature of the flowing medium. In addition to these causes essentially concerning the flow, environmental influences can also change the parameters of interest, as, for example, a temperature gradient in the mass flowmeter itself, the unintentional mechanical contact of the oscillating components with fixed parts and mechanical tension on the measuring tubes. While some of the aforementioned causal parameters for a change of the system behavior can change within seconds or even fractions of a second, other decisive factors change only very slowly, for example over a time span of many months or years; this includes, for example, erosion, corrosion of measuring tubes as well as sedimentary deposition on the measuring tubes.
A change in the fluid density, for example, causes a change in the oscillating mass of the eigenform of the measuring tube. The filling and emptying of the measuring tube as well as multi-phase flow lead to rapid changes of the damping, caused primarily by secondary flows that are induced by the different densities of the medium phases. Additionally, the viscosity of the medium can influence the damping coefficient of the measuring tube.
The stiffness of the eigenform, however, changes primarily as a function of temperature and temperature gradients as well as through mechanical tension acting on the measuring tube, such as process pressure and pulsations in the medium flow. In addition, the parameters of the Coriolis mass flowmeter change due to further influencing variables such as sedimentary deposition and erosion (erosion and corrosion).
The aforementioned examples clearly show that in order to achieve an accurate measurement result, it is necessary to know the essential system-describing parameters of the Coriolis mass flowmeter, since, inevitably, erroneous measurement results are achieved without this knowledge and a correspondingly erroneous adoption of the requirements forming the basis of the measurement.
A variety of methods are known in the prior art for determining the parameters of a system. When the structure of the system to be identified has been determined or even has been determined by a—simplified—adoption based on a model, then the required system identification is to be equivalent to the task of parameter identification, namely the identification of the system-determining parameters of the model taken as a basis.
Methods for determining the parameters of a structured system are essentially known from the prior art that work in an open loop; these types of identification methods are not suitable for carrying out a parameter identification on a Coriolis mass flowmeter during operation, at least not during controlled operation. One method for parameter identification is based on the measurement of the frequency response on the Coriolis mass flowmeter in open loop having deterministic signals. In addition, the oscillation driver is struck with a harmonic excitation signal and—after the oscillator has stabilized—the oscillation of the measuring tube is detected according to amplitude and phase as an output signal of the oscillation sensor. By mixing the output signal with a signal orthogonal to the excitation signal and after carrying out the aforementioned measurement with respectively changed measuring frequencies, the frequency response of the Coriolis mass flowmeter or its parts that can be oscillated can finally be determined. The method is very exact, but extremely time-consuming, since the system responses phase out very slowly due to the very weak damping of the measuring tube of the Coriolis mass flowmeter and, correspondingly, the time consumption for determining the parameters is quite high. Beyond that, the method is not suitable for online parameter identification due to its use in open loop.
Other methods are based on parameter identification using measurements of the frequency response using stochastic signals, wherein the Coriolis mass flowmeter is struck by a noise signal for identification. The description of the stochastic signal in a time range occurs using auto- and cross correlation functions, which describe the statistical degree of relationship between signals. Similar to the deterministic signals, a description of stochastic signals is carried out in the frequency range by using the Fourier transformation. Here, the correlations functions are subjected to the Fourier transformation and, in this manner, the corresponding power spectrums are maintained. The correlation of the auto correlation function of the output signal and the cross correlation function between output and excitation signal in the time range is given by the convolution integral with the weighting function of the system. Since the convolution in the time range corresponds to the multiplication in the frequency range, the complex frequency response can be directly calculated from the ratio of the corresponding power spectrum and, with it, corresponding parameters are identified. Compared to frequency response measurement having deterministic signals, this method is quicker due to the simultaneous excitation of the mass flowmeter to be identified in a broad frequency range, but it is also substantially less accurate. Due to the high dynamics of the Coriolis mass flowmeter and due the influence of the measuring operation by the identification, this method can only be applied during regular operation with substantial limitations.
All in all, it has been determined that known—not shown in detail here—methods for parameter identification in Coriolis mass flowmeters are not—or only with substantial limitations—suitable to be carried out during operation of the Coriolis mass flowmeter in closed loop.